Sandra K. Truong

Energy Sorghum—a genetic model for the design of C4 grass bioenergy crops

Sorghum is emerging as an excellent genetic model for the design of C4 grass bioenergy crops. Annual energy Sorghum hybrids also serve as a source of biomass for bioenergy production. Elucidation of Sorghums flowering time gene regulatory network, and identification of complementary alleles for photoperiod sensitivity, enabled large-scale generation of energy Sorghum hybrids for testing and commercial use. Energy Sorghum hybrids with long vegetative growth phases were found to accumulate more than twice as much biomass as grain Sorghum, owing to extended growing seasons, greater light interception, and higher radiation use efficiency. High biomass yield, efficient nitrogen recycling, and preferential accumulation of stem biomass with low nitrogen content contributed to energy Sorghums elevated nitrogen use efficiency. Sorghums integrated genetics-genomics-breeding platform, diverse germplasm, and the opportunity for annual testing of new genetic designs in controlled environments and in multiple field locations is aiding fundamental discovery, and accelerating the improvement of biomass yield and optimization of composition for biofuels production. Recent advances in wide hybridization between Sorghum and other C4 grasses could allow the deployment of improved genetic designs of annual energy Sorghums in the form of wide-hybrid perennial crops. The current trajectory of energy Sorghum genetic improvement indicates that it will be possible to sustainably produce biofuels from C4 grass bioenergy crops that are cost competitive with petroleum-based transportation fuels.

Harnessing Genetic Variation in Leaf Angle to Increase Productivity of Sorghum bicolor

The efficiency with which a plant intercepts solar radiation is determined primarily by its architecture. Understanding the genetic regulation of plant architecture and how changes in architecture affect performance can be used to improve plant productivity. Leaf inclination angle, the angle at which a leaf emerges with respect to the stem, is a feature of plant architecture that influences how a plant canopy intercepts solar radiation. Here we identify extensive genetic variation for leaf inclination angle in the crop plant Sorghum bicolor, a C4 grass species used for the production of grain, forage, and bioenergy. Multiple genetic loci that regulate leaf inclination angle were identified in recombinant inbred line populations of grain and bioenergy sorghum. Alleles of sorghum dwarf-3, a gene encoding a P-glycoprotein involved in polar auxin transport, are shown to change leaf inclination angle by up to 34° (0.59 rad). The impact of heritable variation in leaf inclination angle on light interception in sorghum canopies was assessed using functional-structural plant models and field experiments. Smaller leaf inclination angles caused solar radiation to penetrate deeper into the canopy, and the resulting redistribution of light is predicted to increase the biomass yield potential of bioenergy sorghum by at least 3%. These results show that sorghum leaf angle is a heritable trait regulated by multiple loci and that genetic variation in leaf angle can be used to modify plant architecture to improve sorghum crop performance.

Resolution of Genetic Map Expansion Caused by Excess Heterozygosity in Plant Recombinant Inbred Populations

Recombinant inbred populations of many plant species exhibit more heterozygosity than expected under the Mendelian model of segregation. This segregation distortion causes the overestimation of recombination frequencies and consequent genetic map expansion. Here we build upon existing genetic models of differential zygotic viability to model a heterozygote fitness term and calculate expected genotypic proportions in recombinant inbred populations propagated by selfing. We implement this model using the existing open-source genetic map construction code base for R/qtl to estimate recombination fractions. Finally, we show that accounting for excess heterozygosity in a sorghum recombinant inbred mapping population shrinks the genetic map by 213 cM (a 13% decrease corresponding to 4.26 fewer recombinations per meiosis). More accurate estimates of linkage benefit linkage-based analyses used in the identification and utilization of causal genetic variation.

3D sorghum reconstructions from depth images identify QTL regulating shoot architecture

A phenotyping platform that generates 3D plant reconstructions identifies genetic loci regulating shoot architecture in the agriculturally important crop sorghum. Dissecting the genetic basis of complex traits is aided by frequent and nondestructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of sorghum (Sorghum bicolor), an important grain, forage, and bioenergy crop, at multiple developmental time points from a greenhouse-grown recombinant inbred line population. A semiautomated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci for standard measures of shoot architecture, such as shoot height, leaf angle, and leaf length, and for novel composite traits, such as shoot compactness. The phenotypic variability associated with some of the quantitative trait loci displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquire shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits.

Identification of Dw1, a Regulator of Sorghum Stem Internode Length

Sorghum is an important C4 grain and grass crop used for food, feed, forage, sugar, and biofuels. In its native Africa, sorghum landraces often grow to approximately 3–4 meters in height. Following introduction into the U.S., shorter, early flowering varieties were identified and used for production of grain. Quinby and Karper identified allelic variation at four loci designated Dw1-Dw4 that regulated plant height by altering the length of stem internodes. The current study used a map-based cloning strategy to identify the gene corresponding to Dw1. Hegari (Dw1dw2Dw3dw4) and 80M (dw1dw2Dw3dw4) were crossed and F2 and HIF derived populations used for QTL mapping. Genetic analysis identified four QTL for internode length in this population, Dw1 on SBI-09, Dw2 on SBI-06, and QTL located on SBI-01 and SBI-07. The QTL on SBI-07 was ~3 Mbp upstream of Dw3 and interacted with Dw1. Dw1 was also found to contribute to the variation in stem weight in the population. Dw1 was fine mapped to an interval of ~33 kbp using HIFs segregating only for Dw1. A polymorphism in an exon of Sobic.009G229800 created a stop codon that truncated the encoded protein in 80M (dw1). This polymorphism was not present in Hegari (Dw1) and no other polymorphisms in the delimited Dw1 locus altered coding regions. The recessive dw1 allele found in 80M was traced to Dwarf Yellow Milo, the progenitor of grain sorghum genotypes identified as dw1. Dw1 encodes a putative membrane protein of unknown function that is highly conserved in plants.

RIG: Recalibration and Interrelation of Genomic Sequence Data with the GATK

Recent advances in variant calling made available in the Genome Analysis Toolkit (GATK) enable the use of validated single-nucleotide polymorphisms and indels to improve variant calling. However, large collections of variants for this purpose often are unavailable to research communities. We introduce a workflow to generate reliable collections of single-nucleotide polymorphisms and indels by leveraging available genomic resources to inform variant calling using the GATK. The workflow is demonstrated for the crop plant Sorghum bicolor by (i) generating an initial set of variants using reduced representation sequence data from an experimental cross and association panels, (ii) using the initial variants to inform variant calling from whole-genome sequence data of resequenced individuals, and (iii) using variants identified from whole-genome sequence data for recalibration of the reduced representation sequence data. The reliability of variants called with the workflow is verified by comparison with genetically mappable variants from an independent sorghum experimental cross. Comparison with a recent sorghum resequencing study shows that the workflow identifies an additional 1.62 million high-confidence variants from the same sequence data. Finally, the workflow’s performance is validated using Arabidopsis sequence data, yielding variant call sets with 95% sensitivity and 99% positive predictive value. The Recalibration and Interrelation of genomic sequence data with the GATK (RIG) workflow enables the GATK to accurately identify genetic variation in organisms lacking validated variant resources.

Genetic Determinants of Cell Size at Birth and Their Impact on Cell Cycle Progression in Saccharomyces cerevisiae

In most cases, cells must increase their size before they can divide. Hence, a small size has been used often as a phenotype for mutants that accelerate initiation of division, such as the celebrated WHI mutants of budding yeast. Recently, we measured the DNA content of all nonessential gene deletion strains in Saccharomyces cerevisiae. Surprisingly, there was little, if any, correlation between mean cell size and cell-cycle progression. Here, we examine this issue further, providing the first systematic analysis of genetic determinants of the cell size at birth. We found that although a large birth size strongly correlates with a large mean size, the converse relationship (i.e., small birth size vs. small mean size) is not as strong. Our data also suggest that mutants that are born large do not have a significant advantage for faster cell-cycle progression. In contrast, mutants that are born small are more likely to progress slower in the cell cycle. The majority of gene deletions that displayed such phenotypes affect protein synthesis or ribosome biogenesis. Overall, our data suggest that birth size may be a more informative parameter for cell-cycle progression than the mean size of a proliferating cell population. In contrast to WHI phenotype expectations, a small size is more likely to be associated with delayed cell-cycle progression.

Sorghum Dw2 Encodes a Protein Kinase Regulator of Stem Internode Length

Sorghum is an important C4 grass crop grown for grain, forage, sugar, and bioenergy production. While tall, late flowering landraces are commonly grown in Africa, short early flowering varieties were selected in US grain sorghum breeding programs to reduce lodging and to facilitate machine harvesting. Four loci have been identified that affect stem length (Dw1-Dw4). Subsequent research showed that Dw3 encodes an ABCB1 auxin transporter and Dw1 encodes a highly conserved protein involved in the regulation of cell proliferation. In this study, Dw2 was identified by fine-mapping and further confirmed by sequencing the Dw2 alleles in Dwarf Yellow Milo and Double Dwarf Yellow Milo, the progenitor genotypes where the recessive allele of dw2 originated. The Dw2 locus was determined to correspond to Sobic.006G067700, a gene that encodes a protein kinase that is homologous to KIPK, a member of the AGCVIII subgroup of the AGC protein kinase family in Arabidopsis.

Bioenergy Sorghum Crop Model Predicts VPD-Limited Transpiration Traits Enhance Biomass Yield in Water-Limited Environments

Bioenergy sorghum is targeted for production in water-limited annual cropland therefore traits that improve plant water capture, water use efficiency, and resilience to water deficit are necessary to maximize productivity. A crop modeling framework, APSIM, was adapted to predict the growth and biomass yield of energy sorghum and to identify potentially useful traits for crop improvement. APSIM simulations of energy sorghum development and biomass accumulation replicated results from field experiments across multiple years, patterns of rainfall, and irrigation schemes. Modeling showed that energy sorghums long duration of vegetative growth increased water capture and biomass yield by ~30% compared to short season crops in a water-limited production region. Additionally, APSIM was extended to enable modeling of VPD-limited transpiration traits that reduce crop water use under high vapor pressure deficits (VPDs). The response of transpiration rate to increasing VPD was modeled as a linear response until a VPD threshold was reached, at which the slope of the response decreases, representing a range of responses to VPD observed in sorghum germplasm. Simulation results indicated that the VPD-limited transpiration trait is most beneficial in hot and dry regions of production where crops are exposed to extended periods without rainfall during the season or to a terminal drought. In these environments, slower but more efficient transpiration increases biomass yield and prevents or delays the exhaustion of soil water and onset of leaf senescence. The VPD-limited transpiration responses observed in sorghum germplasm increased biomass accumulation by 20% in years with lower summer rainfall, and the ability to drastically reduce transpiration under high VPD conditions could increase biomass by 6% on average across all years. This work indicates that the productivity and resilience of bioenergy sorghum grown in water-limited environments could be further enhanced by development of genotypes with optimized VPD-limited transpiration traits and deployment of these crops in water limited growing environments. The energy sorghum model and VPD-limited transpiration trait implementation are made available to simulate performance in other target environments.

3D sorghum reconstructions from depth images enable identification of quantitative trait loci regulating shoot architecture

Dissecting the genetic basis of complex traits is aided by frequent and non-destructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of Sorghum bicolor, an important grain, forage, and bioenergy crop, at multiple developmental timepoints from a greenhouse-grown recombinant inbred line population. A semi-automated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci (QTL) for standard measures of shoot architecture such as shoot height, leaf angle and leaf length, and for novel composite traits such as shoot compactness. The phenotypic variability associated with some of the QTL displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquire shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits.